US20030163054A1 - Monitoring respiration based on plethysmographic heart rate signal - Google Patents

Monitoring respiration based on plethysmographic heart rate signal Download PDF

Info

Publication number
US20030163054A1
US20030163054A1 US10/081,719 US8171902A US2003163054A1 US 20030163054 A1 US20030163054 A1 US 20030163054A1 US 8171902 A US8171902 A US 8171902A US 2003163054 A1 US2003163054 A1 US 2003163054A1
Authority
US
United States
Prior art keywords
signal
heart rate
patient
pleth
set forth
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
US10/081,719
Other versions
US6702752B2 (en
Inventor
Andreas Dekker
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Datex Ohmeda Inc
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to US10/081,719 priority Critical patent/US6702752B2/en
Assigned to DATEX-OHMEDA, INC. reassignment DATEX-OHMEDA, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: DEKKER, ANDREAS LUBBERTUS ALOYSIUS JOHANNES
Priority to JP2003570689A priority patent/JP2005535359A/en
Priority to PCT/US2003/004836 priority patent/WO2003071938A1/en
Priority to EP20030713516 priority patent/EP1485009A1/en
Priority to AU2003217564A priority patent/AU2003217564A1/en
Priority to CNA038083272A priority patent/CN1646055A/en
Publication of US20030163054A1 publication Critical patent/US20030163054A1/en
Priority to US10/790,950 priority patent/US7001337B2/en
Publication of US6702752B2 publication Critical patent/US6702752B2/en
Application granted granted Critical
Anticipated expiration legal-status Critical
Expired - Lifetime legal-status Critical Current

Links

Images

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02416Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/08Detecting, measuring or recording devices for evaluating the respiratory organs
    • A61B5/0816Measuring devices for examining respiratory frequency
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters

Definitions

  • the present invention relates, in general, to the noninvasive monitoring of respiration rate based on optical (visible and/or non-visible spectrum) signals and, in particular, to monitoring respiration based on the processing of received optical signals to identify heart rate variability associated with respiration.
  • the invention can be readily implemented in connection with pulse oximetry instruments so as to expand the utility of such instruments.
  • Photoplethysmography relates to the use of optical signals transmitted through or reflected by a patient's blood, e.g., arterial blood or perfused tissue, for monitoring a physiological parameter of a patient.
  • a patient's blood e.g., arterial blood or perfused tissue
  • Such monitoring is possible because the optical signal is modulated by interaction with the patient's blood. That is, interaction with the patient's blood generally involving a wavelength and/or time dependent attenuation due to absorption, reflection and/or diffusion, imparts characteristics to the transmitted signal that can be analyzed to yield information regarding the physiological parameter of interest.
  • Such monitoring of patients is highly desirable because it is noninvasive, typically yields substantially instantaneous and accurate results, and utilizes minimal medical resources, thereby proving to be cost effective.
  • Pulse oximeters determine an oxygen saturation level of a patient's blood, or related analyte values, based on transmission/absorption characteristics of light transmitted through or reflected from the patient's tissue.
  • pulse oximeters generally include a probe for attaching to a patient's appendage such as a finger, earlobe or nasal septum.
  • the probe is used to transmit pulsed optical signals of at least two wavelengths, typically red and infrared, through the patient's appendage.
  • the transmitted signals are received by a detector that provides an analog electrical output signal representative of the received optical signals.
  • A/D analog to digital
  • a single multi-channel digital signal may be received by the digital processing unit or separate digital signals for each channel may be received.
  • the digital processing unit may be used to separate the received signal into separate channel components.
  • the digital processing unit processes digital information representing each of the channels.
  • Such digital information defines input photoplethysmographic signals or “pleths.” These pleths generally contain two components.
  • the first component of interest is a low frequency or substantially invariant component in relation to the time increments considered for blood oxygen saturation calculations, sometimes termed the “DC component,” which generally corresponds to the attenuation related to the non-pulsatile volume of the perfused tissue and other matter that affects the transmitted plethysmographic signal.
  • the second component sometimes termed the “AC component” generally corresponds to the change in attenuation due to the pulsation of the blood.
  • the AC component represents a varying waveform which corresponds in frequency to that of the heartbeat.
  • the DC component is a more steady baseline component, since the effective volume of the tissue under investigation varies little or at a low frequency if the variations caused by the pulsation of the heart are excluded from consideration.
  • Pulse oximeters typically provide as outputs blood oxygen saturation values and, sometimes, a heart rate and a graphical representation of a pulsatile waveform.
  • the information for generating each of these outputs is generally obtained from the AC component of the pleth.
  • some pulse oximeters attempt to filter the DC component from the pleth, e.g., in order to provide a better digitized AC component waveform.
  • Other pulse oximeters may measure and use the DC component, e.g., to normalize measured differential values obtained from the AC component or to provide measurements relevant to motion or other noise corrections.
  • the present invention is directed to monitoring patient respiration based on a pleth signal.
  • the invention thus provides important diagnostic or monitoring information noninvasively.
  • various aspects of the invention can be implemented using one or more channels and/or other components of a conventional pulse oximeter, thereby providing additional functionality to instruments that are widely available and trusted, as well as providing access to important information for treatment of patients on a cost-effective basis.
  • a pleth signal is analyzed to identify a heart rate variability parameter associated with respiration rate.
  • the associated process involves obtaining a pleth signal, processing the pleth signal to obtain heart rate samples, monitoring the heart rate samples to identify a heart rate variability, and determining a respiration rate based on the heart rate variability. It is known that heart rate varies with the respiration cycle, an effect called Respiratory Sinus Arrhythmia.
  • the present invention provides a robust process for monitoring this effect and determining respiration rate based on pleth signals.
  • a novel processor and pulse oximeter incorporating such processing are also provided in accordance with the present invention.
  • the step of obtaining a pleth signal generally involves receiving a digital signal representative of an optical signal modulated based on interaction with perfused tissue of a patient.
  • a digital signal representative of an optical signal modulated based on interaction with perfused tissue of a patient.
  • Such a signal may be provided using components of a conventional pulse oximeter.
  • Pulse oximeters typically transmit red and infrared signals, thereby yielding red and infrared pleths.
  • each of these pleths generally has a fundamental frequency corresponding to the patient's heart rate. Accordingly, either pleth can be used to yield the desired heart rate information.
  • the infrared channel typically has the stronger pleth waveform and may be preferred for heart rate calculations.
  • the red pleth may be preferred.
  • a combination of the two signals may provide a better waveform for heart rate analysis than either signal alone.
  • the pleth may be processed to obtain heart rate samples in a variety of ways.
  • the pleth is generally a periodic signal having a fundamental frequency corresponding to the patient's heart rate.
  • heart rate may be determined by performing peak-to-peak measurements on the pleth to determine the pulse period and, hence, pulse frequency. For example, such maxima may be obtained by identifying a change in sign of differential values between successive samples or groups of samples along the pleth or of a function fitted to the pleth.
  • other points on the waveform, such as nominal zero (or average pleth value) crossings may be monitored. Such zero crossings would be expected to have a frequency of twice the heart rate.
  • Such period measurements can be complicated due to the typically noisy waveform of the pleths. Accordingly, multiple waveforms may be utilized.
  • the heart rate calculations may be performed in the frequency domain.
  • a processor may be configured to obtain a Fourier transform of the pleth. Once the Fourier transform is obtained, the pulse rate can be identified as the fundamental frequency of the pleth corresponding to the patient's heart rate.
  • the heart rate once the heart rate is determined, it can be monitored to identify low frequency variations associated with respiration. In particular, oscillatory variations having a frequency of between about 0.15 and 0.5 Hz and, especially, between about 0.2 and 0.4 Hz, are indicative of respiration rate. This range may be expanded to 0-5 Hz to accommodate the higher respiration rates of newborns.
  • One or more filters may be used in determining respiration rate information based on a pleth signal in accordance with the present invention.
  • an adaptive filter may be used to track the fundamental frequency of the pleth and, hence, the patient's pulse rate.
  • a filter may function as a narrow band pass filter having a band pass that is centered on the fundamental frequency of the pleth.
  • the transfer function of the filter may be varied, e.g., based on analysis of successive waveforms, to track the changing fundamental frequency.
  • the filter or associated logic may thus be adapted to output a time series of pulse rate values.
  • Such a time series of pulse rate values may be filtered using a static band pass filter having a pass band including the noted frequencies of interest, or using an adaptive filter that tracks a selected spectral peak of the time series to provide an output indicative of respiration rate.
  • a static band pass filter having a pass band including the noted frequencies of interest
  • an adaptive filter that tracks a selected spectral peak of the time series to provide an output indicative of respiration rate.
  • the present invention is based in part on a recognition that the pleth signal includes a variety of information in addition to the pulsatile waveform that is generally the focus of plethysmographic processing.
  • the pleth signal includes at least three additional or related components: 1) a component related to respiration or the “respiration wave”, 2) a low frequency component associated with the autonomic nervous system or vaso motor center, sometimes termed the “Mayer wave,” and 3) a very low frequency component which is associated with temperature control.
  • the Mayer wave relates to a low frequency variation in blood pressure, heart rate, and/or vaso constriction.
  • the first two components noted above have particular significance for diagnostic and patient monitoring purposes.
  • the amplitude and frequency of the Mayer wave are seen to change in connection with hypertension, sudden cardiac death, ventricular tachycardia, coronary artery disease, myocardial infarction, heart failure, diabetes, and autonomic neuropathy and after heart transplantation.
  • Respiration rate is monitored during a variety of medical procedures, for example, as an indication of a patient's stress levels and to identify patient respiratory distress. It is expected that both the Mayer and respiration waves influence heart rate (and related parameters such as variations in blood pressure and blood volume) by direct influence on the vaso motor center. In the latter case, this is by a “spillover” from the breathing center to the vaso motor center, which increases heart rate during inspiration.
  • a difficulty associated with obtaining physiological parameter information based on the Mayer wave and the respiration wave relates to distinguishing the effects associated with these waves, particularly in view of the fact that each of these waves can occur within overlapping frequency ranges.
  • respiration information is obtained by monitoring heart rate variability within a specific frequency band as noted above.
  • a frequency range having a lower end of preferably at least about 0.15 Hz, for example, 0.15-0.5 interference due to Mayer wave effects can generally be minimized.
  • Still better results may be obtained by monitoring a range between about 0.2-0.4 Hz or, especially, about 0.3 Hz.
  • the transfer function may be limited to track the respiration related peak only within these ranges using 0.3 Hz as an initial condition.
  • FIG. 1 is a schematic diagram of a pulse oximeter in accordance with the present invention
  • FIG. 2 illustrates the waveform of a pleth that may be used to obtain respiratory information in accordance with the present invention
  • FIG. 3 illustrates a pleth power spectrum showing the respiration related peak that is used in accordance with the present invention
  • FIG. 4 illustrates a heart rate time series generated using an appropriate filter in accordance with the present invention
  • FIG. 5 is a pleth power spectrum illustrating a transfer function of a filter in accordance with the present invention
  • FIG. 6 is a respiratory power spectrum illustrating a transfer function of another filter in accordance with the present invention.
  • FIG. 7 is a flow chart illustrating a process for using a pleth signal to monitor respiration in accordance with the present invention.
  • FIG. 8 illustrates a signal processing system in accordance with the present invention.
  • the present invention relates to obtaining physiological parameter information for a patient based on an analysis of a pleth involving distinguishing an effect associated with a Mayer wave component from an effect associated with a respiration wave component.
  • the invention is described in the context of an implementation utilizing components of a conventional pulse oximeter.
  • the invention has particular advantages in this regard as such an implementation enhances the functionality of conventional pulse oximeters and provides important physiological parameter information in a cost effective manner.
  • various aspects of the invention are not limited to such a pulse oximeter or other multi-channel signal implementation and the invention may be embodied in a dedicated single or multi-channel photoplethysmography instrument. Accordingly, the following discussion should be understood as exemplifying the invention and not by way of limitation.
  • the oximeter 100 generally includes an instrument housing 102 and a probe 104 for attachment to a finger 101 or other appendage of a patient under analysis.
  • the probe 104 includes two or more sources 106 and a detector 110 . It will be appreciated that either or both of these components may alternatively be located in the housing 102 and may be optically connected to the probe 104 by fiber optics or the like. Additionally, the sources 106 and/or detector 110 may be located in the cable or other coupling operatively between the probe 104 and the housing 102 .
  • the sources 106 are driven by source drives 108 .
  • the drives 108 serve to modulate the signals 103 in any of various ways.
  • the signals 103 transmitted by the sources 106 may be time division multiplexed, frequency division multiplexed, code division multiplexed, or the like. Such multiplexing facilitates separation of the signals from each of the channels during hardware or software based signal processing.
  • the sources 106 provide two or more channels of signals 103 . Each channel has a unique spectral content, e.g., wavelength or wavelength band. In the illustrated embodiment, two sources 106 are shown; one of the sources may have a red-centered wavelength and the other may have an infrared-centered wavelength.
  • the signals 103 may be transmitted through or reflected by the patient's tissue. In either case, the signals are modulated by the patient's tissue to provide information regarding blood oxygen saturation in a manner that is well known.
  • the transmitted signals 103 are received by the detector 110 which, in the illustrated embodiment, provides an analog current output signal 105 representative of the detected signals 103 .
  • This detector signal 105 is then processed by signal processing module 112 .
  • the processing module 112 may include a number of components that may be embodied in software, firmware and/or hardware. These components may include components for amplifying the signal 105 and converting the signal from a current signal to a voltage signal, filtering the signal to remove certain components of noise and otherwise conditioning the signal.
  • the signal processing module 112 also includes an analog to digital converter for converting the signal into a digital signal and a demultiplexer component for providing two separate output signals 118 or pleths that generally correspond to the two separate channel signals 103 . These pleths 118 are then used by oxygenation calculation module 116 to compute a value related to blood oxygen saturation, e.g., a blood oxygen saturation percentage.
  • a blood oxygen saturation percentage e.g., a blood oxygen saturation percentage.
  • FIG. 2 illustrates an exemplary waveform of a pleth as such information may be obtained by the processor of a pulse oximeter.
  • information may be obtained as a digital signal output by the A/D converter, i.e., a time series of values related to the detector output.
  • the pleth corresponding to either of the oximetry channels, or a combination of the channels, may be used in accordance with the present invention. It is desirable to obtain a strong pleth signal so that the waveform and pulse rate can be accurately identified. Accordingly, for normally oxygenated patients, the infrared channel pleth may be utilized. For poorly oxygenated patients, the red pleth may be preferred.
  • a cut off oxygenation level such as 85% may be used in determining whether to use the infrared or red pleth.
  • the two pleth signals may be mathematically blended, depending on the current oxygenation level to obtain an optimized pleth for subsequent analysis in accordance with the present invention.
  • Appropriate techniques for obtaining an optimized pleth signal are disclosed in U.S. patent application Ser. No. 09/975,289, which is disclosed herein by reference.
  • the pleth signal includes a pulsatile component having a period designated T p .
  • This period corresponds to the patient's heart rate.
  • the heart rate can be determined by monitoring this pleth in a variety of ways such as identifying a change in sign of a differential value of the waveform (e.g., to perform a peak-to-peak period measurement or peak-to-trough 1 ⁇ 2 period measurement), tracking crossings of an average value indicated by A, or, as will be discussed in more detail below, by using a filter to track the fundamental frequency of the pleth.
  • FIG. 3 shows an exemplary pleth power spectrum.
  • the spectrum is characterized by three discrete peaks. These include a peak typically around 0.3 Hz-0.5 Hz, a peak typically around 0.1 Hz and a peak below 0.05 Hz.
  • the peak below 0.05 Hz is generally linked with vaso motor control and temperature control.
  • the peak at around 0.1 Hz is generally associated with the Mayer wave.
  • this phenomenon is not well understood but has been correlated to hypertension, sudden cardiac death, ventricular tachycardia, coronary artery disease, myocardial infarction, heart failure, diabetes, and autonomic neuropathy and has been seen to change after heart transplantation.
  • the remaining peak, at about 0.3-0.5 Hz is believed to be correlated with respiration and is of particular interest for purposes of the present invention. It will be appreciated that this peak may be as high as 1 Hz or greater for newborns.
  • FIG. 4 graphically illustrates the respiratory Sinus Arrhythmia phenomenon associated with the above noted respiration wave.
  • FIG. 4 is a graph plotting the output of a heart rate filter, as will be discussed below, against time.
  • the result is a periodic waveform having a period designated T B .
  • T B This generally corresponds to a reduction in heart rate during the expiration portion of the respiratory cycle and an increase in heart rate during the inspiration portion of the cycle.
  • the period of this waveform generally corresponds to the respiration rate and is tracked using a pulse oximeter in accordance with the present invention.
  • respiration rate can be monitored by: 1) determining heart rate based on an analysis of the pleth signal, 2) monitoring this heart rate over time to obtain a time series heart rate values, and 3) analyzing the time series heart rate values to identify a respiration rate. These steps can be executed using adaptive filters and/or static band pass filters as discussed below.
  • FIG. 5 illustrates a pleth power spectrum.
  • a power spectrum may be obtained by configuring the oximeter processor to mathematically obtain a Fourier transform of the time domain pleth signal.
  • the pleth power spectrum has a fundamental frequency at t 0 corresponding to the patient's heart rate. Additional peaks of the illustrated power spectrum relate to harmonics thereof.
  • the present invention utilizes an adaptive filter adapted to function as a band pass filter having a narrow band pass encompassing the fundamental frequency. The transfer function of this filter is generally indicated by function 500 .
  • a variety of different types of filters may be used in this regard. Generally, such filters track the fundamental frequency of a signal based on certain programmed information regarding the nature of the signal as well as by monitoring successive signal waveforms. Such filters are robust in operation and can provide a continually updated output, in this case, regarding pulse rate. Thus, such a filter can provide as an output a time series of pulse rate values such as illustrated in FIG. 4.
  • An additional digital filter can be used to track respiration rate.
  • the output of the heart rate filter can be processed to provide a respiratory power spectrum as shown in FIG. 6.
  • the oximeter processor can be configured to perform a Fourier transform on the time series of pulse rate values output by the heart rate filter.
  • the resulting respiratory power spectrum includes a frequency peak correlated to the respiration rate designated as t 0 .
  • the additional peaks shown in the power spectrum of FIG. 6 relate to harmonics thereof or other heart rate variations.
  • An adaptive filter having a transfer function, generally indicated by function 600 can be used to track the fundamental frequency.
  • Such a filter may be similar to the heart rate filter as described above and is programmed to adaptively track the noted frequency of the respiratory power spectrum which corresponds to respiration rate.
  • the output of this filter is a periodically updated respiration rate value.
  • a static band pass filter may be used to isolate the peak related to respiration and, hence, identify the respiration rate.
  • Such a filter may have a pass band of 0-0.5 Hz or, to accommodate neonatal applications, 0-1.5 Hz.
  • FIG. 7 is a flow chart illustrating a process for determining respiration rate based on pleth signals in accordance with the present invention.
  • the process 700 is initiated by obtaining a detector output or pleth signal. In the context of a pulse oximeter, this may involve receiving the digital output from an A/D converter that reflects the detector signal, demodulating this signal to obtain individual channel components and selecting a pleth for further processing.
  • the selected pleth may be one of the channels or an optimized pleth based on both of the channel components.
  • the pleth is then filtered ( 704 ) to obtain a time series of heart rate values. These values are monitored ( 706 ) over time to obtain a heart rate signal.
  • the heart rate signal is then filtered ( 708 ) to identify a frequency peak correlated to respiration.
  • the frequency of this peak is then output ( 710 ) as a respiration rate.
  • This respiration rate may be displayed in the display area of a conventional pulse oximeter programmed to provide such information.
  • the illustrative unit 800 includes an A/D converter 802 .
  • the A/D converter receives an analog signal representative of the optical signal received by the pulse oximeter detector. This analog input signal is processed by the converter ( 802 ) to provide a digital detector signal 803 .
  • the digital detector signal 803 is then processed by demodulator 804 to provide two separate channel signals designated channel A ( 805 ) and channel B ( 807 ), that may correspond, for example, to the red and infrared channels of the pulse oximeter. These channel signals are then processed by the optimized pleth generator 806 to provide an optimized pleth waveform 809 .
  • the optimized pleth waveform may correspond to either of the channel signals or a combination thereof.
  • This optimized waveform 809 is processed by a heart rate filter in order to track the fundamental frequency of the waveform which corresponds to the patient's heart rate.
  • the output from the heart rate filter 808 is a time series of heart rate values 811 .
  • This time series heart rate values is then processed by a respiration rate filter 810 which tracks a selected frequency of the corresponding spectrum to determine respiration rate 813 .
  • the patient's respiration rate 813 may be periodically output to a user via a display 812 .

Abstract

A pleth signal is analyzed to identify a heart rate variability parameter associated with respiration rate. In one embodiment, an associated process involves obtaining a photoplethysmograpic signal, processing the pleth signal to obtain heart rate samples, monitoring the heart rate sample to identify a heart rate variability associated with respiration, and determining a respiration rate based on the heart rate variability. The photoplethysmographic signal may be based on one or more channel signals of a conventional pulse oximeter. The invention thus allows for noninvasive monitoring of respiration rate and expands the functionality of pulse oximeters.

Description

    FIELD OF THE INVENTION
  • The present invention relates, in general, to the noninvasive monitoring of respiration rate based on optical (visible and/or non-visible spectrum) signals and, in particular, to monitoring respiration based on the processing of received optical signals to identify heart rate variability associated with respiration. The invention can be readily implemented in connection with pulse oximetry instruments so as to expand the utility of such instruments. [0001]
  • BACKGROUND OF THE INVENTION
  • Photoplethysmography relates to the use of optical signals transmitted through or reflected by a patient's blood, e.g., arterial blood or perfused tissue, for monitoring a physiological parameter of a patient. Such monitoring is possible because the optical signal is modulated by interaction with the patient's blood. That is, interaction with the patient's blood generally involving a wavelength and/or time dependent attenuation due to absorption, reflection and/or diffusion, imparts characteristics to the transmitted signal that can be analyzed to yield information regarding the physiological parameter of interest. Such monitoring of patients is highly desirable because it is noninvasive, typically yields substantially instantaneous and accurate results, and utilizes minimal medical resources, thereby proving to be cost effective. [0002]
  • A common type of photoplethysmographic instrument is the pulse oximeter. Pulse oximeters determine an oxygen saturation level of a patient's blood, or related analyte values, based on transmission/absorption characteristics of light transmitted through or reflected from the patient's tissue. In particular, pulse oximeters generally include a probe for attaching to a patient's appendage such as a finger, earlobe or nasal septum. The probe is used to transmit pulsed optical signals of at least two wavelengths, typically red and infrared, through the patient's appendage. The transmitted signals are received by a detector that provides an analog electrical output signal representative of the received optical signals. By processing the electrical signal and analyzing signal values for each of the wavelengths at different portions of a patient's pulse cycle, information can be obtained regarding blood oxygen saturation. [0003]
  • The algorithms for determining blood oxygen saturation related values are normally implemented in a digital processing unit. Accordingly, one or more analog to digital (A/D) converters are generally interposed between the detector and the digital processing unit. Depending on the specific system architecture employed, a single multi-channel digital signal may be received by the digital processing unit or separate digital signals for each channel may be received. In the former case, the digital processing unit may be used to separate the received signal into separate channel components. Thus, in either case, the digital processing unit processes digital information representing each of the channels. [0004]
  • Such digital information defines input photoplethysmographic signals or “pleths.” These pleths generally contain two components. The first component of interest is a low frequency or substantially invariant component in relation to the time increments considered for blood oxygen saturation calculations, sometimes termed the “DC component,” which generally corresponds to the attenuation related to the non-pulsatile volume of the perfused tissue and other matter that affects the transmitted plethysmographic signal. The second component, sometimes termed the “AC component,” generally corresponds to the change in attenuation due to the pulsation of the blood. In general, the AC component represents a varying waveform which corresponds in frequency to that of the heartbeat. In contrast, the DC component is a more steady baseline component, since the effective volume of the tissue under investigation varies little or at a low frequency if the variations caused by the pulsation of the heart are excluded from consideration. [0005]
  • Pulse oximeters typically provide as outputs blood oxygen saturation values and, sometimes, a heart rate and a graphical representation of a pulsatile waveform. The information for generating each of these outputs is generally obtained from the AC component of the pleth. In this regard, some pulse oximeters attempt to filter the DC component from the pleth, e.g., in order to provide a better digitized AC component waveform. Other pulse oximeters may measure and use the DC component, e.g., to normalize measured differential values obtained from the AC component or to provide measurements relevant to motion or other noise corrections. Generally, though, conventional pulse oximeters do not monitor variations in the DC component of a pleth or pleths to obtain physiological parameter information in addition to the outputs noted above. Although it has been proposed to use pulse oximeters to monitor other parameters including respiration rate, it is apparent that such proposed uses have not gained general commercial acceptance. [0006]
  • SUMMARY OF THE INVENTION
  • The present invention is directed to monitoring patient respiration based on a pleth signal. The invention thus provides important diagnostic or monitoring information noninvasively. Moreover, various aspects of the invention can be implemented using one or more channels and/or other components of a conventional pulse oximeter, thereby providing additional functionality to instruments that are widely available and trusted, as well as providing access to important information for treatment of patients on a cost-effective basis. [0007]
  • In accordance with one aspect of the present invention, a pleth signal is analyzed to identify a heart rate variability parameter associated with respiration rate. The associated process involves obtaining a pleth signal, processing the pleth signal to obtain heart rate samples, monitoring the heart rate samples to identify a heart rate variability, and determining a respiration rate based on the heart rate variability. It is known that heart rate varies with the respiration cycle, an effect called Respiratory Sinus Arrhythmia. The present invention provides a robust process for monitoring this effect and determining respiration rate based on pleth signals. A novel processor and pulse oximeter incorporating such processing are also provided in accordance with the present invention. [0008]
  • The step of obtaining a pleth signal generally involves receiving a digital signal representative of an optical signal modulated based on interaction with perfused tissue of a patient. Such a signal may be provided using components of a conventional pulse oximeter. Pulse oximeters typically transmit red and infrared signals, thereby yielding red and infrared pleths. Either or both of these pleths may be utilized in accordance with the present invention. In particular, each of these pleths generally has a fundamental frequency corresponding to the patient's heart rate. Accordingly, either pleth can be used to yield the desired heart rate information. In general, for normally oxygenated patients, the infrared channel typically has the stronger pleth waveform and may be preferred for heart rate calculations. For poorly oxygenated patients, the red pleth may be preferred. In many cases, a combination of the two signals may provide a better waveform for heart rate analysis than either signal alone. [0009]
  • The pleth may be processed to obtain heart rate samples in a variety of ways. As noted above, the pleth is generally a periodic signal having a fundamental frequency corresponding to the patient's heart rate. Accordingly, heart rate may be determined by performing peak-to-peak measurements on the pleth to determine the pulse period and, hence, pulse frequency. For example, such maxima may be obtained by identifying a change in sign of differential values between successive samples or groups of samples along the pleth or of a function fitted to the pleth. Alternatively, other points on the waveform, such as nominal zero (or average pleth value) crossings may be monitored. Such zero crossings would be expected to have a frequency of twice the heart rate. Such period measurements can be complicated due to the typically noisy waveform of the pleths. Accordingly, multiple waveforms may be utilized. [0010]
  • Additionally, the heart rate calculations may be performed in the frequency domain. In this regard, a processor may be configured to obtain a Fourier transform of the pleth. Once the Fourier transform is obtained, the pulse rate can be identified as the fundamental frequency of the pleth corresponding to the patient's heart rate. In any case, once the heart rate is determined, it can be monitored to identify low frequency variations associated with respiration. In particular, oscillatory variations having a frequency of between about 0.15 and 0.5 Hz and, especially, between about 0.2 and 0.4 Hz, are indicative of respiration rate. This range may be expanded to 0-5 Hz to accommodate the higher respiration rates of newborns. [0011]
  • One or more filters may be used in determining respiration rate information based on a pleth signal in accordance with the present invention. In this regard, an adaptive filter may be used to track the fundamental frequency of the pleth and, hence, the patient's pulse rate. For example, such a filter may function as a narrow band pass filter having a band pass that is centered on the fundamental frequency of the pleth. The transfer function of the filter may be varied, e.g., based on analysis of successive waveforms, to track the changing fundamental frequency. The filter or associated logic may thus be adapted to output a time series of pulse rate values. Such a time series of pulse rate values, whether obtained as an output of an adaptive filter system or otherwise, may be filtered using a static band pass filter having a pass band including the noted frequencies of interest, or using an adaptive filter that tracks a selected spectral peak of the time series to provide an output indicative of respiration rate. Such filtering provides a fast, robust and computationally efficient mechanism for noninvasively monitoring patient respiration based on pleth signals. [0012]
  • The present invention is based in part on a recognition that the pleth signal includes a variety of information in addition to the pulsatile waveform that is generally the focus of plethysmographic processing. In particular, it has been recognized that the pleth signal includes at least three additional or related components: 1) a component related to respiration or the “respiration wave”, 2) a low frequency component associated with the autonomic nervous system or vaso motor center, sometimes termed the “Mayer wave,” and 3) a very low frequency component which is associated with temperature control. Regarding the second of these, the origin and nature of the Mayer wave is not fully settled. For present purposes, the Mayer wave relates to a low frequency variation in blood pressure, heart rate, and/or vaso constriction. [0013]
  • The first two components noted above have particular significance for diagnostic and patient monitoring purposes. In particular, the amplitude and frequency of the Mayer wave are seen to change in connection with hypertension, sudden cardiac death, ventricular tachycardia, coronary artery disease, myocardial infarction, heart failure, diabetes, and autonomic neuropathy and after heart transplantation. Respiration rate is monitored during a variety of medical procedures, for example, as an indication of a patient's stress levels and to identify patient respiratory distress. It is expected that both the Mayer and respiration waves influence heart rate (and related parameters such as variations in blood pressure and blood volume) by direct influence on the vaso motor center. In the latter case, this is by a “spillover” from the breathing center to the vaso motor center, which increases heart rate during inspiration. [0014]
  • A difficulty associated with obtaining physiological parameter information based on the Mayer wave and the respiration wave relates to distinguishing the effects associated with these waves, particularly in view of the fact that each of these waves can occur within overlapping frequency ranges. In accordance with the present invention, respiration information is obtained by monitoring heart rate variability within a specific frequency band as noted above. In particular, by monitoring in a frequency range having a lower end of preferably at least about 0.15 Hz, for example, 0.15-0.5, interference due to Mayer wave effects can generally be minimized. Still better results may be obtained by monitoring a range between about 0.2-0.4 Hz or, especially, about 0.3 Hz. In the case of tracking respiration rate using an adaptive filter relative to a time series of pulse rate values or a corresponding frequency spectrum, the transfer function may be limited to track the respiration related peak only within these ranges using 0.3 Hz as an initial condition. [0015]
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • For a more complete understanding of the present invention and further advantages thereof, reference is now made to the following detailed description, taken in conjunction with the drawings, in which: [0016]
  • FIG. 1 is a schematic diagram of a pulse oximeter in accordance with the present invention; [0017]
  • FIG. 2 illustrates the waveform of a pleth that may be used to obtain respiratory information in accordance with the present invention; [0018]
  • FIG. 3 illustrates a pleth power spectrum showing the respiration related peak that is used in accordance with the present invention; [0019]
  • FIG. 4 illustrates a heart rate time series generated using an appropriate filter in accordance with the present invention; [0020]
  • FIG. 5 is a pleth power spectrum illustrating a transfer function of a filter in accordance with the present invention; [0021]
  • FIG. 6 is a respiratory power spectrum illustrating a transfer function of another filter in accordance with the present invention; [0022]
  • FIG. 7 is a flow chart illustrating a process for using a pleth signal to monitor respiration in accordance with the present invention; and [0023]
  • FIG. 8 illustrates a signal processing system in accordance with the present invention.[0024]
  • DETAILED DESCRIPTION
  • The present invention relates to obtaining physiological parameter information for a patient based on an analysis of a pleth involving distinguishing an effect associated with a Mayer wave component from an effect associated with a respiration wave component. In the following discussion, the invention is described in the context of an implementation utilizing components of a conventional pulse oximeter. The invention has particular advantages in this regard as such an implementation enhances the functionality of conventional pulse oximeters and provides important physiological parameter information in a cost effective manner. However, it will be appreciated that various aspects of the invention are not limited to such a pulse oximeter or other multi-channel signal implementation and the invention may be embodied in a dedicated single or multi-channel photoplethysmography instrument. Accordingly, the following discussion should be understood as exemplifying the invention and not by way of limitation. [0025]
  • Referring to FIG. 1, a schematic diagram of a [0026] pulse oximeter 100 in accordance with the present invention is shown. The oximeter 100 generally includes an instrument housing 102 and a probe 104 for attachment to a finger 101 or other appendage of a patient under analysis. In the illustrated embodiment, the probe 104 includes two or more sources 106 and a detector 110. It will be appreciated that either or both of these components may alternatively be located in the housing 102 and may be optically connected to the probe 104 by fiber optics or the like. Additionally, the sources 106 and/or detector 110 may be located in the cable or other coupling operatively between the probe 104 and the housing 102. The sources 106 are driven by source drives 108. The drives 108 serve to modulate the signals 103 in any of various ways. In this regard, the signals 103 transmitted by the sources 106 may be time division multiplexed, frequency division multiplexed, code division multiplexed, or the like. Such multiplexing facilitates separation of the signals from each of the channels during hardware or software based signal processing. The sources 106 provide two or more channels of signals 103. Each channel has a unique spectral content, e.g., wavelength or wavelength band. In the illustrated embodiment, two sources 106 are shown; one of the sources may have a red-centered wavelength and the other may have an infrared-centered wavelength.
  • The [0027] signals 103 may be transmitted through or reflected by the patient's tissue. In either case, the signals are modulated by the patient's tissue to provide information regarding blood oxygen saturation in a manner that is well known. The transmitted signals 103 are received by the detector 110 which, in the illustrated embodiment, provides an analog current output signal 105 representative of the detected signals 103. This detector signal 105 is then processed by signal processing module 112. The processing module 112 may include a number of components that may be embodied in software, firmware and/or hardware. These components may include components for amplifying the signal 105 and converting the signal from a current signal to a voltage signal, filtering the signal to remove certain components of noise and otherwise conditioning the signal. In the illustrated embodiment, the signal processing module 112 also includes an analog to digital converter for converting the signal into a digital signal and a demultiplexer component for providing two separate output signals 118 or pleths that generally correspond to the two separate channel signals 103. These pleths 118 are then used by oxygenation calculation module 116 to compute a value related to blood oxygen saturation, e.g., a blood oxygen saturation percentage. A number of algorithms for performing such calculations are known and such calculation techniques are disclosed in U.S. Pat. Nos. 5,934,277 by Mortz and 5,842,979 by Jarman, both of which are incorporated herein by reference.
  • FIG. 2 illustrates an exemplary waveform of a pleth as such information may be obtained by the processor of a pulse oximeter. In particular, such information may be obtained as a digital signal output by the A/D converter, i.e., a time series of values related to the detector output. Such values are shown graphically in FIG. 2. As noted above, the pleth corresponding to either of the oximetry channels, or a combination of the channels, may be used in accordance with the present invention. It is desirable to obtain a strong pleth signal so that the waveform and pulse rate can be accurately identified. Accordingly, for normally oxygenated patients, the infrared channel pleth may be utilized. For poorly oxygenated patients, the red pleth may be preferred. In this regard, a cut off oxygenation level such as 85% may be used in determining whether to use the infrared or red pleth. Alternatively, the two pleth signals may be mathematically blended, depending on the current oxygenation level to obtain an optimized pleth for subsequent analysis in accordance with the present invention. Appropriate techniques for obtaining an optimized pleth signal are disclosed in U.S. patent application Ser. No. 09/975,289, which is disclosed herein by reference. [0028]
  • As shown in FIG. 2, the pleth signal includes a pulsatile component having a period designated T[0029] p. This period corresponds to the patient's heart rate. The heart rate can be determined by monitoring this pleth in a variety of ways such as identifying a change in sign of a differential value of the waveform (e.g., to perform a peak-to-peak period measurement or peak-to-trough ½ period measurement), tracking crossings of an average value indicated by A, or, as will be discussed in more detail below, by using a filter to track the fundamental frequency of the pleth.
  • In accordance with the present invention, the patient's respiration is monitored by tracking low frequency heart rate changes. FIG. 3 shows an exemplary pleth power spectrum. The spectrum is characterized by three discrete peaks. These include a peak typically around 0.3 Hz-0.5 Hz, a peak typically around 0.1 Hz and a peak below 0.05 Hz. The peak below 0.05 Hz is generally linked with vaso motor control and temperature control. The peak at around 0.1 Hz is generally associated with the Mayer wave. As noted above, this phenomenon is not well understood but has been correlated to hypertension, sudden cardiac death, ventricular tachycardia, coronary artery disease, myocardial infarction, heart failure, diabetes, and autonomic neuropathy and has been seen to change after heart transplantation. The remaining peak, at about 0.3-0.5 Hz is believed to be correlated with respiration and is of particular interest for purposes of the present invention. It will be appreciated that this peak may be as high as 1 Hz or greater for newborns. [0030]
  • FIG. 4 graphically illustrates the respiratory Sinus Arrhythmia phenomenon associated with the above noted respiration wave. In particular, FIG. 4 is a graph plotting the output of a heart rate filter, as will be discussed below, against time. As shown, the result is a periodic waveform having a period designated T[0031] B. This generally corresponds to a reduction in heart rate during the expiration portion of the respiratory cycle and an increase in heart rate during the inspiration portion of the cycle. The period of this waveform generally corresponds to the respiration rate and is tracked using a pulse oximeter in accordance with the present invention.
  • From the foregoing discussion, it will be appreciated that respiration rate can be monitored by: 1) determining heart rate based on an analysis of the pleth signal, 2) monitoring this heart rate over time to obtain a time series heart rate values, and 3) analyzing the time series heart rate values to identify a respiration rate. These steps can be executed using adaptive filters and/or static band pass filters as discussed below. [0032]
  • FIG. 5 illustrates a pleth power spectrum. Such a power spectrum may be obtained by configuring the oximeter processor to mathematically obtain a Fourier transform of the time domain pleth signal. As shown, the pleth power spectrum has a fundamental frequency at t[0033] 0 corresponding to the patient's heart rate. Additional peaks of the illustrated power spectrum relate to harmonics thereof. The present invention utilizes an adaptive filter adapted to function as a band pass filter having a narrow band pass encompassing the fundamental frequency. The transfer function of this filter is generally indicated by function 500. A variety of different types of filters may be used in this regard. Generally, such filters track the fundamental frequency of a signal based on certain programmed information regarding the nature of the signal as well as by monitoring successive signal waveforms. Such filters are robust in operation and can provide a continually updated output, in this case, regarding pulse rate. Thus, such a filter can provide as an output a time series of pulse rate values such as illustrated in FIG. 4.
  • An additional digital filter can be used to track respiration rate. In particular, the output of the heart rate filter can be processed to provide a respiratory power spectrum as shown in FIG. 6. For example, the oximeter processor can be configured to perform a Fourier transform on the time series of pulse rate values output by the heart rate filter. The resulting respiratory power spectrum includes a frequency peak correlated to the respiration rate designated as t[0034] 0. The additional peaks shown in the power spectrum of FIG. 6 relate to harmonics thereof or other heart rate variations. An adaptive filter having a transfer function, generally indicated by function 600, can be used to track the fundamental frequency. Such a filter may be similar to the heart rate filter as described above and is programmed to adaptively track the noted frequency of the respiratory power spectrum which corresponds to respiration rate. The output of this filter is a periodically updated respiration rate value. Alternatively, a static band pass filter may be used to isolate the peak related to respiration and, hence, identify the respiration rate. Such a filter may have a pass band of 0-0.5 Hz or, to accommodate neonatal applications, 0-1.5 Hz.
  • FIG. 7 is a flow chart illustrating a process for determining respiration rate based on pleth signals in accordance with the present invention. The [0035] process 700 is initiated by obtaining a detector output or pleth signal. In the context of a pulse oximeter, this may involve receiving the digital output from an A/D converter that reflects the detector signal, demodulating this signal to obtain individual channel components and selecting a pleth for further processing. The selected pleth may be one of the channels or an optimized pleth based on both of the channel components. The pleth is then filtered (704) to obtain a time series of heart rate values. These values are monitored (706) over time to obtain a heart rate signal. The heart rate signal is then filtered (708) to identify a frequency peak correlated to respiration. The frequency of this peak is then output (710) as a respiration rate. This respiration rate may be displayed in the display area of a conventional pulse oximeter programmed to provide such information.
  • The corresponding components of a pulse oximeter processing unit are illustrated in FIG. 8. The [0036] illustrative unit 800 includes an A/D converter 802. The A/D converter receives an analog signal representative of the optical signal received by the pulse oximeter detector. This analog input signal is processed by the converter (802) to provide a digital detector signal 803. The digital detector signal 803 is then processed by demodulator 804 to provide two separate channel signals designated channel A (805) and channel B (807), that may correspond, for example, to the red and infrared channels of the pulse oximeter. These channel signals are then processed by the optimized pleth generator 806 to provide an optimized pleth waveform 809. As discussed above, the optimized pleth waveform may correspond to either of the channel signals or a combination thereof. This optimized waveform 809 is processed by a heart rate filter in order to track the fundamental frequency of the waveform which corresponds to the patient's heart rate. The output from the heart rate filter 808 is a time series of heart rate values 811. This time series heart rate values is then processed by a respiration rate filter 810 which tracks a selected frequency of the corresponding spectrum to determine respiration rate 813. The patient's respiration rate 813 may be periodically output to a user via a display 812.
  • While various embodiments of the present invention have been described in detail, it is apparent that further modifications and adaptations of the invention will occur to those skilled in the art. However, it is to be expressly understood that such modifications and adaptations are within the spirit and scope of the present invention. [0037]

Claims (24)

What is claimed:
1. A method for use in monitoring a patient, comprising the steps of:
obtaining a photoplethysmographic (“pleth”) signal that is modulated based on interaction of a transmitted optical signal with a patient's blood;
first processing said pleth signal to obtain heart rate information regarding a heart rate of said patient; and
second processing said heart rate information to obtain respiration information regarding respiration of said patient.
2. A method as set forth in claim 1, wherein said step of obtaining a pleth signal comprises operating a pulse oximeter to obtain a detector signal corresponding to at least one wavelength channel of transmitted light.
3. A method as set forth in claim 1, wherein said step of obtaining a pleth signal comprises operating a pulse oximeter to obtain a detector signal corresponding to at least two different wavelength channels of transmitted light.
4. A method as set forth in claim 3, wherein said step of obtaining comprises selecting a signal component corresponding to one of said two channels as said pleth signal.
5. A method as set forth in claim 3, wherein said step of obtaining comprises processing signal components corresponding to both of said channels to obtain said pleth signal.
6. A method as set forth in claim 1, wherein said step of first processing comprises identifying characteristics of a waveform of said pleth signal corresponding to a pulse cycle of said patient so as to determine one of a period and a frequency of said pulse cycle.
7. A method as set forth in claim 1, wherein said step of first processing comprises performing a spectral analysis of said pleth signal to obtain said heart rate information.
8. A method as set forth in claim 1, wherein said step of first processing comprises using a filter to identify a spectral peak corresponding to said heart rate of said patient.
9. A method as set forth in claim 1, wherein said step of first processing comprises obtaining a heart rate signal reflecting a time series of heart rate values for said patient.
10. A method as set forth in claim 1, wherein said step of second processing comprises identifying a variation in said heart rate of said patient associated with said respiration.
11. A method as set forth in claim 1, wherein said step of second processing comprises filtering said heart rate information to identify a variation therein within a frequency range between about 0-1.5 Hz.
12. A method as set forth in claim 11, wherein said variation is within a frequency range between about 0.15 and 0.5 Hz.
13. A method as set forth in claim 11, wherein said variation is within a frequency range between about 0.2-0.4 Hz.
14. A method as set forth in claim 1, further comprising the step of providing an output indicative of a respiration rate of said patient.
15. A method for use in monitoring a patient, comprising the steps of:
obtaining a photoplethysmographic (“pleth”) signal that is modulated based on interaction of a transmitted optical signal with a patient's blood;
processing said pleth signal using at least one filter so as to distinguish a signal component of interest having a frequency corresponding to a respiration rate of said patient from a potentially interfering signal component having a frequency between 0-0.5 Hz; and
providing an output indicative of said respiration rate of said patient based on said signal component of interest.
16. A method as set forth in claim 15, wherein said step of processing comprises first processing said pleth signal to obtain a heart rate signal and second processing said heart rate signal to identify said frequency corresponding to said respiration rate.
17. A method as set forth in claim 15, wherein said filter is used to identify a heart rate of a patient.
18. A method as set forth in claim 15, wherein said filter is used to identify said respiration rate from a heart rate signal.
19. An apparatus for use in monitoring a patient, comprising:
a port for receiving a photoplethysmograph (“pleth”) signal that is modulated based on interaction of a transmitted optical signal with a patient's blood; and
a processor operative for first processing said pleth signal to obtain heart rate information regarding a heart rate of said patient and second processing said heart rate information to obtain respiration information regarding respiration of said patient.
20. An apparatus as set forth in claim 19, wherein said apparatus further comprises a source for transmitting an optical signal including at least one wavelength channel relative to a patient, a detector for receiving said transmitted optical signal and a signal processing module for processing a signal from said detector to provide said pleth signal.
21. An apparatus as set forth in claim 20, wherein said processor includes a module for identifying characteristics of a waveform of said pleth signal corresponding to a pulse cycle of said patient so as to determine one of a period and a frequency of said pulse cycle.
22. An apparatus as set forth in claim 19, wherein said processor is operative to perform a spectral analysis of said pleth signal to obtain said heart rate information.
23. An apparatus as set forth in claim 19, wherein said processor includes a filter for identifying a spectral peak corresponding to said heart rate of said patient.
24. An apparatus as set forth in claim 19, wherein said processor is operative for identifying a variation in said heart rate of said patient associated with said respiration.
US10/081,719 2002-02-22 2002-02-22 Monitoring respiration based on plethysmographic heart rate signal Expired - Lifetime US6702752B2 (en)

Priority Applications (7)

Application Number Priority Date Filing Date Title
US10/081,719 US6702752B2 (en) 2002-02-22 2002-02-22 Monitoring respiration based on plethysmographic heart rate signal
AU2003217564A AU2003217564A1 (en) 2002-02-22 2003-02-19 Monitoring physiological parameters based on variations in a photoplethysmographic signal
PCT/US2003/004836 WO2003071938A1 (en) 2002-02-22 2003-02-19 Monitoring physiological parameters based on variations in a photoplethysmographic signal
EP20030713516 EP1485009A1 (en) 2002-02-22 2003-02-19 Monitoring physiological parameters based on variations in a photoplethysmographic signal
JP2003570689A JP2005535359A (en) 2002-02-22 2003-02-19 Monitoring physiological parameters based on fluctuations in photoplethysmographic signals
CNA038083272A CN1646055A (en) 2002-02-22 2003-02-19 Monitoring physiological parameters based on variations in a photoplethysmographic signal
US10/790,950 US7001337B2 (en) 2002-02-22 2004-03-02 Monitoring physiological parameters based on variations in a photoplethysmographic signal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US10/081,719 US6702752B2 (en) 2002-02-22 2002-02-22 Monitoring respiration based on plethysmographic heart rate signal

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US10/081,887 Continuation-In-Part US6805673B2 (en) 2002-02-22 2002-02-22 Monitoring mayer wave effects based on a photoplethysmographic signal

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US10/790,950 Continuation-In-Part US7001337B2 (en) 2002-02-22 2004-03-02 Monitoring physiological parameters based on variations in a photoplethysmographic signal

Publications (2)

Publication Number Publication Date
US20030163054A1 true US20030163054A1 (en) 2003-08-28
US6702752B2 US6702752B2 (en) 2004-03-09

Family

ID=27752996

Family Applications (1)

Application Number Title Priority Date Filing Date
US10/081,719 Expired - Lifetime US6702752B2 (en) 2002-02-22 2002-02-22 Monitoring respiration based on plethysmographic heart rate signal

Country Status (1)

Country Link
US (1) US6702752B2 (en)

Cited By (55)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040225207A1 (en) * 2003-05-09 2004-11-11 Sang-Kon Bae Ear type apparatus for measuring a bio signal and measuring method therefor
US20050209521A1 (en) * 2002-05-29 2005-09-22 Joni Kettunen Procedure for deriving reliable information on respiratory activity from heart period measurement
US20060004405A1 (en) * 2001-10-18 2006-01-05 Amr Salahieh Vascular embolic filter devices and methods of use therefor
US20060009971A1 (en) * 2004-06-30 2006-01-12 Kushner William M Method and apparatus for characterizing inhalation noise and calculating parameters based on the characterization
US20060009970A1 (en) * 2004-06-30 2006-01-12 Harton Sara M Method for detecting and attenuating inhalation noise in a communication system
US20060020451A1 (en) * 2004-06-30 2006-01-26 Kushner William M Method and apparatus for equalizing a speech signal generated within a pressurized air delivery system
US20070021673A1 (en) * 2004-01-27 2007-01-25 Cardiometer Ltd. Method and system for cardiovascular system diagnosis
EP1757225A1 (en) * 2005-08-26 2007-02-28 Nihon Kohden Corporation Apparataus and method for measuring pulse rate
US20070056582A1 (en) * 2005-03-18 2007-03-15 Michael Wood Methods and devices for relieving stress
GB2438070A (en) * 2006-05-12 2007-11-14 Suunto Oy Determining energy consumption during exercise from respiratory frequency derived from heart rate measurements
US20080249422A1 (en) * 2007-04-05 2008-10-09 Stephen Bennett Elliott Method and system for improving physiologic status and health via assessment of the dynamic respiratory arterial pressure wave using plethysmographic technique
US20100004552A1 (en) * 2006-12-21 2010-01-07 Fresenius Medical Care Deutschland Gmbh Method and device for the determination of breath frequency
US7691049B2 (en) 2004-03-18 2010-04-06 Respironics, Inc. Methods and devices for relieving stress
US20100106030A1 (en) * 2008-10-23 2010-04-29 Mason Gregory R Method and system for automated measurement of pulsus paradoxus
US20100113904A1 (en) * 2008-11-05 2010-05-06 Nellcor Puritan Bennett Llc System And Method For Facilitating Observation Of Monitored Physiologic Data
WO2010082200A1 (en) * 2009-01-14 2010-07-22 Widemed Ltd. Method and system for detecting a respiratory signal
US20100222655A1 (en) * 2003-12-01 2010-09-02 Ric Investments, Llc Apparatus and method for monitoring pressure related changes in the extra-thoracic arterial circulatory system
US20100298730A1 (en) * 2007-07-30 2010-11-25 Oxford Biosignals Limited Method and apparatus for measuring breathing rate
US20120172688A1 (en) * 2007-12-06 2012-07-05 Los Angeles Biomedical Research Institute At Harbor-Ucla Medical Center Method and system for detection of respiratory variation in plethysmographic oximetry
US8398555B2 (en) 2008-09-10 2013-03-19 Covidien Lp System and method for detecting ventilatory instability
US8641631B2 (en) 2004-04-08 2014-02-04 Masimo Corporation Non-invasive monitoring of respiratory rate, heart rate and apnea
US20140039283A1 (en) * 2012-07-31 2014-02-06 Periodic Breathing Foundation System for analyzing oximetry data
US8755871B2 (en) 2011-11-30 2014-06-17 Covidien Lp Systems and methods for detecting arrhythmia from a physiological signal
US8880576B2 (en) 2011-09-23 2014-11-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US8880155B2 (en) 2012-02-24 2014-11-04 Covidien Lp Hypovolemia diagnosis technique
US9066680B1 (en) 2009-10-15 2015-06-30 Masimo Corporation System for determining confidence in respiratory rate measurements
US9119597B2 (en) 2011-09-23 2015-09-01 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9179876B2 (en) 2012-04-30 2015-11-10 Nellcor Puritan Bennett Ireland Systems and methods for identifying portions of a physiological signal usable for determining physiological information
US9247896B2 (en) 2012-01-04 2016-02-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using phase locked loop
US9307928B1 (en) * 2010-03-30 2016-04-12 Masimo Corporation Plethysmographic respiration processor
US20160143566A1 (en) * 2014-11-20 2016-05-26 Qualcomm Incorporated Circuitry to Allow Low Current Operation of a Device Capable of Determining a Blood Property
US9402554B2 (en) 2011-09-23 2016-08-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
EP3066978A1 (en) * 2003-12-30 2016-09-14 Beta Biomed Services, Inc. Method and system of monitoring respiration in an individual
US9554712B2 (en) 2013-02-27 2017-01-31 Covidien Lp Systems and methods for generating an artificial photoplethysmograph signal
US9560978B2 (en) 2013-02-05 2017-02-07 Covidien Lp Systems and methods for determining respiration information from a physiological signal using amplitude demodulation
US20170055846A1 (en) * 2015-08-28 2017-03-02 Oslermd, Inc. Methods and apparatuses for measuring multiple vital signs based on arterial pressure waveforms
CN106725491A (en) * 2017-02-16 2017-05-31 王丽燕 A kind of respiratory rate method for determining child patient
US9668695B2 (en) 2004-08-11 2017-06-06 University Of Florida Research Foundation, Inc. Pulse oximeter probes and methods for using the same
US9675274B2 (en) 2011-09-23 2017-06-13 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9687159B2 (en) 2013-02-27 2017-06-27 Covidien Lp Systems and methods for determining physiological information by identifying fiducial points in a physiological signal
US9693709B2 (en) 2011-09-23 2017-07-04 Nellcot Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9693736B2 (en) 2011-11-30 2017-07-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using historical distribution
US9724016B1 (en) 2009-10-16 2017-08-08 Masimo Corp. Respiration processor
US9801579B2 (en) 2012-03-19 2017-10-31 Fujitsu Limited Arousal-level determining apparatus and arousal-level determining method
US9848820B2 (en) 2014-01-07 2017-12-26 Covidien Lp Apnea analysis system and method
US9901308B2 (en) 2014-02-20 2018-02-27 Covidien Lp Systems and methods for filtering autocorrelation peaks and detecting harmonics
US10022068B2 (en) 2013-10-28 2018-07-17 Covidien Lp Systems and methods for detecting held breath events
US20180333102A1 (en) * 2015-12-01 2018-11-22 Koninklijke Philips N.V. Device, system and method for determining vital sign information of a subject
US10159842B2 (en) 2015-08-28 2018-12-25 Cardiac Pacemakers, Inc. System and method for detecting tamponade
US20190261890A1 (en) * 2015-06-01 2019-08-29 Pixart Imaging Inc. Optical respiration rate detection device
US10441181B1 (en) 2013-03-13 2019-10-15 Masimo Corporation Acoustic pulse and respiration monitoring system
US11006843B1 (en) 2020-08-20 2021-05-18 Cloud Dx, Inc. System and method of determining breathing rates from oscillometric data
US11229374B2 (en) 2006-12-09 2022-01-25 Masimo Corporation Plethysmograph variability processor
US11259749B2 (en) 2004-08-11 2022-03-01 Koninklijke Philips N.V. Pulse oximeter probes and methods for using the same
US11272859B1 (en) 2020-08-20 2022-03-15 Cloud Dx, Inc. System and method of determining respiratory status from oscillometric data

Families Citing this family (143)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6018673A (en) 1996-10-10 2000-01-25 Nellcor Puritan Bennett Incorporated Motion compatible sensor for non-invasive optical blood analysis
US6675031B1 (en) 1999-04-14 2004-01-06 Mallinckrodt Inc. Method and circuit for indicating quality and accuracy of physiological measurements
AU5359901A (en) 2000-04-17 2001-10-30 Vivometrics Inc Systems and methods for ambulatory monitoring of physiological signs
US7666151B2 (en) * 2002-11-20 2010-02-23 Hoana Medical, Inc. Devices and methods for passive patient monitoring
US6748254B2 (en) 2001-10-12 2004-06-08 Nellcor Puritan Bennett Incorporated Stacked adhesive optical sensor
WO2003071938A1 (en) * 2002-02-22 2003-09-04 Datex-Ohmeda, Inc. Monitoring physiological parameters based on variations in a photoplethysmographic signal
KR100455289B1 (en) * 2002-03-16 2004-11-08 삼성전자주식회사 Method of diagnosing using a ray and apparatus thereof
US6783498B2 (en) * 2002-03-26 2004-08-31 Vivometrics, Inc. Method and system for extracting cardiac parameters from plethysmographic signals
US8790272B2 (en) * 2002-03-26 2014-07-29 Adidas Ag Method and system for extracting cardiac parameters from plethysmographic signals
US7407486B2 (en) * 2002-10-14 2008-08-05 Ge Healthcare Finland Oy Method and an apparatus for pulse plethysmograph based detection of nociception during anesthesia or sedation
US7190986B1 (en) 2002-10-18 2007-03-13 Nellcor Puritan Bennett Inc. Non-adhesive oximeter sensor for sensitive skin
US8255029B2 (en) 2003-02-27 2012-08-28 Nellcor Puritan Bennett Llc Method of analyzing and processing signals
WO2004080300A1 (en) * 2003-03-12 2004-09-23 Yale University Method of assesing blood volume using photoelectric plethysmography
US20080082018A1 (en) * 2003-04-10 2008-04-03 Sackner Marvin A Systems and methods for respiratory event detection
US7689271B1 (en) 2003-06-26 2010-03-30 Hoana Medical, Inc. Non-invasive heart rate and respiration measurements from extremities
JP5466351B2 (en) 2003-11-18 2014-04-09 アディダス アーゲー Method and system for processing data from mobile physiological monitoring
US7771364B2 (en) * 2004-01-27 2010-08-10 Spirocor Ltd. Method and system for cardiovascular system diagnosis
US7435214B2 (en) * 2004-01-29 2008-10-14 Cannuflow, Inc. Atraumatic arthroscopic instrument sheath
US9492084B2 (en) 2004-06-18 2016-11-15 Adidas Ag Systems and methods for monitoring subjects in potential physiological distress
US9504410B2 (en) * 2005-09-21 2016-11-29 Adidas Ag Band-like garment for physiological monitoring
US20060253010A1 (en) * 2004-09-28 2006-11-09 Donald Brady Monitoring device, method and system
US7887492B1 (en) 2004-09-28 2011-02-15 Impact Sports Technologies, Inc. Monitoring device, method and system
US20060079794A1 (en) * 2004-09-28 2006-04-13 Impact Sports Technologies, Inc. Monitoring device, method and system
AU2011203234B2 (en) * 2004-10-06 2013-01-10 Resmed Limited Method and Apparatus for Non-Invasive Monitoring of Respiratory Parameters in Sleep Disordered Breathing
NZ589369A (en) * 2004-10-06 2012-03-30 Resmed Ltd Using oximeter and airflow signals to process two signals and with further processor to generate results based on the two signals
US7578793B2 (en) * 2004-11-22 2009-08-25 Widemed Ltd. Sleep staging based on cardio-respiratory signals
EP1848336A4 (en) * 2005-02-07 2009-11-11 Widemed Ltd Detection and monitoring of stress events during sleep
US7635337B2 (en) * 2005-03-24 2009-12-22 Ge Healthcare Finland Oy Determination of clinical stress of a subject in pulse oximetry
WO2006113804A2 (en) * 2005-04-20 2006-10-26 Vivometrics, Inc. Systems and methods for non-invasive physiological monitoring of non-human animals
CA2606699C (en) 2005-05-20 2017-04-18 Vivometrics, Inc. Methods and systems for determining dynamic hyperinflation
US8033996B2 (en) 2005-07-26 2011-10-11 Adidas Ag Computer interfaces including physiologically guided avatars
US7657295B2 (en) 2005-08-08 2010-02-02 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US7657294B2 (en) 2005-08-08 2010-02-02 Nellcor Puritan Bennett Llc Compliant diaphragm medical sensor and technique for using the same
US7590439B2 (en) 2005-08-08 2009-09-15 Nellcor Puritan Bennett Llc Bi-stable medical sensor and technique for using the same
US20070060808A1 (en) 2005-09-12 2007-03-15 Carine Hoarau Medical sensor for reducing motion artifacts and technique for using the same
US7904130B2 (en) 2005-09-29 2011-03-08 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US8092379B2 (en) 2005-09-29 2012-01-10 Nellcor Puritan Bennett Llc Method and system for determining when to reposition a physiological sensor
US7869850B2 (en) 2005-09-29 2011-01-11 Nellcor Puritan Bennett Llc Medical sensor for reducing motion artifacts and technique for using the same
US7899510B2 (en) 2005-09-29 2011-03-01 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US7486979B2 (en) 2005-09-30 2009-02-03 Nellcor Puritan Bennett Llc Optically aligned pulse oximetry sensor and technique for using the same
US20070077200A1 (en) * 2005-09-30 2007-04-05 Baker Clark R Method and system for controlled maintenance of hypoxia for therapeutic or diagnostic purposes
US7555327B2 (en) 2005-09-30 2009-06-30 Nellcor Puritan Bennett Llc Folding medical sensor and technique for using the same
US8062221B2 (en) 2005-09-30 2011-11-22 Nellcor Puritan Bennett Llc Sensor for tissue gas detection and technique for using the same
US8233954B2 (en) 2005-09-30 2012-07-31 Nellcor Puritan Bennett Llc Mucosal sensor for the assessment of tissue and blood constituents and technique for using the same
US7881762B2 (en) 2005-09-30 2011-02-01 Nellcor Puritan Bennett Llc Clip-style medical sensor and technique for using the same
US7483731B2 (en) 2005-09-30 2009-01-27 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US8762733B2 (en) * 2006-01-30 2014-06-24 Adidas Ag System and method for identity confirmation using physiologic biometrics to determine a physiologic fingerprint
US20070270671A1 (en) * 2006-04-10 2007-11-22 Vivometrics, Inc. Physiological signal processing devices and associated processing methods
US8073518B2 (en) 2006-05-02 2011-12-06 Nellcor Puritan Bennett Llc Clip-style medical sensor and technique for using the same
US8475387B2 (en) * 2006-06-20 2013-07-02 Adidas Ag Automatic and ambulatory monitoring of congestive heart failure patients
US8145288B2 (en) 2006-08-22 2012-03-27 Nellcor Puritan Bennett Llc Medical sensor for reducing signal artifacts and technique for using the same
US8219170B2 (en) 2006-09-20 2012-07-10 Nellcor Puritan Bennett Llc System and method for practicing spectrophotometry using light emitting nanostructure devices
US8359079B2 (en) * 2006-09-21 2013-01-22 Starr Life Sciences Corporation Pulse oximetry system and techniques for deriving cardiac and breathing parameters from extra-thoracic blood flow measurements
US20080076991A1 (en) * 2006-09-21 2008-03-27 Starr Life Sciences Corp. Medical display devices for cardiac and breathing parameters derived from extra-thoracic blood flow measurements
US7922666B2 (en) * 2006-09-21 2011-04-12 Starr Life Sciences Corporation Pulse oximeter based techniques for controlling anesthesia levels and ventilation levels in subjects
US8195264B2 (en) 2006-09-22 2012-06-05 Nellcor Puritan Bennett Llc Medical sensor for reducing signal artifacts and technique for using the same
US8396527B2 (en) 2006-09-22 2013-03-12 Covidien Lp Medical sensor for reducing signal artifacts and technique for using the same
US8175671B2 (en) 2006-09-22 2012-05-08 Nellcor Puritan Bennett Llc Medical sensor for reducing signal artifacts and technique for using the same
US7869849B2 (en) 2006-09-26 2011-01-11 Nellcor Puritan Bennett Llc Opaque, electrically nonconductive region on a medical sensor
US7574245B2 (en) 2006-09-27 2009-08-11 Nellcor Puritan Bennett Llc Flexible medical sensor enclosure
US8123695B2 (en) * 2006-09-27 2012-02-28 Nellcor Puritan Bennett Llc Method and apparatus for detection of venous pulsation
US7796403B2 (en) 2006-09-28 2010-09-14 Nellcor Puritan Bennett Llc Means for mechanical registration and mechanical-electrical coupling of a faraday shield to a photodetector and an electrical circuit
US7890153B2 (en) 2006-09-28 2011-02-15 Nellcor Puritan Bennett Llc System and method for mitigating interference in pulse oximetry
US8068891B2 (en) 2006-09-29 2011-11-29 Nellcor Puritan Bennett Llc Symmetric LED array for pulse oximetry
US7680522B2 (en) 2006-09-29 2010-03-16 Nellcor Puritan Bennett Llc Method and apparatus for detecting misapplied sensors
US7476131B2 (en) 2006-09-29 2009-01-13 Nellcor Puritan Bennett Llc Device for reducing crosstalk
US7684842B2 (en) 2006-09-29 2010-03-23 Nellcor Puritan Bennett Llc System and method for preventing sensor misuse
US8175667B2 (en) 2006-09-29 2012-05-08 Nellcor Puritan Bennett Llc Symmetric LED array for pulse oximetry
US9833184B2 (en) * 2006-10-27 2017-12-05 Adidas Ag Identification of emotional states using physiological responses
US8646447B2 (en) * 2006-11-13 2014-02-11 Resmed Limited Systems, methods, and/or apparatuses for non-invasive monitoring of respiratory parameters in sleep disordered breathing
KR100882440B1 (en) * 2006-11-27 2009-02-06 삼성전자주식회사 Biosignal-detecting apparatus and mrthod of operating the apparatus
US8157730B2 (en) 2006-12-19 2012-04-17 Valencell, Inc. Physiological and environmental monitoring systems and methods
US8652040B2 (en) 2006-12-19 2014-02-18 Valencell, Inc. Telemetric apparatus for health and environmental monitoring
US8229530B2 (en) * 2007-03-09 2012-07-24 Nellcor Puritan Bennett Llc System and method for detection of venous pulsation
US8265724B2 (en) 2007-03-09 2012-09-11 Nellcor Puritan Bennett Llc Cancellation of light shunting
US7894869B2 (en) 2007-03-09 2011-02-22 Nellcor Puritan Bennett Llc Multiple configuration medical sensor and technique for using the same
US8280469B2 (en) 2007-03-09 2012-10-02 Nellcor Puritan Bennett Llc Method for detection of aberrant tissue spectra
US8221326B2 (en) * 2007-03-09 2012-07-17 Nellcor Puritan Bennett Llc Detection of oximetry sensor sites based on waveform characteristics
US8109882B2 (en) * 2007-03-09 2012-02-07 Nellcor Puritan Bennett Llc System and method for venous pulsation detection using near infrared wavelengths
US20080262326A1 (en) * 2007-04-19 2008-10-23 Starr Life Sciences Corp. Signal Processing Method and Apparatus for Processing a Physiologic Signal such as a Photoplethysmography Signal
US20080300500A1 (en) * 2007-05-30 2008-12-04 Widemed Ltd. Apnea detection using a capnograph
US8251903B2 (en) 2007-10-25 2012-08-28 Valencell, Inc. Noninvasive physiological analysis using excitation-sensor modules and related devices and methods
US8352004B2 (en) 2007-12-21 2013-01-08 Covidien Lp Medical sensor and technique for using the same
US8346328B2 (en) 2007-12-21 2013-01-01 Covidien Lp Medical sensor and technique for using the same
US8366613B2 (en) 2007-12-26 2013-02-05 Covidien Lp LED drive circuit for pulse oximetry and method for using same
US8577434B2 (en) 2007-12-27 2013-11-05 Covidien Lp Coaxial LED light sources
US8452364B2 (en) 2007-12-28 2013-05-28 Covidien LLP System and method for attaching a sensor to a patient's skin
US8442608B2 (en) 2007-12-28 2013-05-14 Covidien Lp System and method for estimating physiological parameters by deconvolving artifacts
US8199007B2 (en) 2007-12-31 2012-06-12 Nellcor Puritan Bennett Llc Flex circuit snap track for a biometric sensor
US8897850B2 (en) 2007-12-31 2014-11-25 Covidien Lp Sensor with integrated living hinge and spring
US8070508B2 (en) 2007-12-31 2011-12-06 Nellcor Puritan Bennett Llc Method and apparatus for aligning and securing a cable strain relief
US8092993B2 (en) 2007-12-31 2012-01-10 Nellcor Puritan Bennett Llc Hydrogel thin film for use as a biosensor
US8437822B2 (en) 2008-03-28 2013-05-07 Covidien Lp System and method for estimating blood analyte concentration
US8112375B2 (en) 2008-03-31 2012-02-07 Nellcor Puritan Bennett Llc Wavelength selection and outlier detection in reduced rank linear models
US7887345B2 (en) 2008-06-30 2011-02-15 Nellcor Puritan Bennett Llc Single use connector for pulse oximetry sensors
US20090326402A1 (en) * 2008-06-30 2009-12-31 Nellcor Puritan Bennett Ireland Systems and methods for determining effort
US8071935B2 (en) 2008-06-30 2011-12-06 Nellcor Puritan Bennett Llc Optical detector with an overmolded faraday shield
US7880884B2 (en) 2008-06-30 2011-02-01 Nellcor Puritan Bennett Llc System and method for coating and shielding electronic sensor components
US20100030040A1 (en) 2008-08-04 2010-02-04 Masimo Laboratories, Inc. Multi-stream data collection system for noninvasive measurement of blood constituents
US8577431B2 (en) 2008-07-03 2013-11-05 Cercacor Laboratories, Inc. Noise shielding for a noninvasive device
US8364220B2 (en) 2008-09-25 2013-01-29 Covidien Lp Medical sensor and technique for using the same
US8914088B2 (en) 2008-09-30 2014-12-16 Covidien Lp Medical sensor and technique for using the same
US8423112B2 (en) 2008-09-30 2013-04-16 Covidien Lp Medical sensor and technique for using the same
US8417309B2 (en) 2008-09-30 2013-04-09 Covidien Lp Medical sensor
US9155493B2 (en) 2008-10-03 2015-10-13 Nellcor Puritan Bennett Ireland Methods and apparatus for calibrating respiratory effort from photoplethysmograph signals
US9011347B2 (en) 2008-10-03 2015-04-21 Nellcor Puritan Bennett Ireland Methods and apparatus for determining breathing effort characteristics measures
ES2336997B1 (en) * 2008-10-16 2011-06-13 Sabirmedical,S.L. SYSTEM AND APPARATUS FOR NON-INVASIVE MEASUREMENT OF BLOOD PRESSURE.
US8788002B2 (en) 2009-02-25 2014-07-22 Valencell, Inc. Light-guiding devices and monitoring devices incorporating same
EP3127476A1 (en) 2009-02-25 2017-02-08 Valencell, Inc. Light-guiding devices and monitoring devices incorporating same
US8452366B2 (en) 2009-03-16 2013-05-28 Covidien Lp Medical monitoring device with flexible circuitry
US8221319B2 (en) 2009-03-25 2012-07-17 Nellcor Puritan Bennett Llc Medical device for assessing intravascular blood volume and technique for using the same
US8509869B2 (en) 2009-05-15 2013-08-13 Covidien Lp Method and apparatus for detecting and analyzing variations in a physiologic parameter
US8634891B2 (en) 2009-05-20 2014-01-21 Covidien Lp Method and system for self regulation of sensor component contact pressure
US8444570B2 (en) * 2009-06-09 2013-05-21 Nellcor Puritan Bennett Ireland Signal processing techniques for aiding the interpretation of respiration signals
US20100331716A1 (en) * 2009-06-26 2010-12-30 Nellcor Puritan Bennett Ireland Methods and apparatus for measuring respiratory function using an effort signal
US20100331715A1 (en) * 2009-06-30 2010-12-30 Nellcor Puritan Bennett Ireland Systems and methods for detecting effort events
US8311601B2 (en) 2009-06-30 2012-11-13 Nellcor Puritan Bennett Llc Reflectance and/or transmissive pulse oximeter
US8505821B2 (en) 2009-06-30 2013-08-13 Covidien Lp System and method for providing sensor quality assurance
US9010634B2 (en) 2009-06-30 2015-04-21 Covidien Lp System and method for linking patient data to a patient and providing sensor quality assurance
US8391941B2 (en) 2009-07-17 2013-03-05 Covidien Lp System and method for memory switching for multiple configuration medical sensor
US8755854B2 (en) 2009-07-31 2014-06-17 Nellcor Puritan Bennett Ireland Methods and apparatus for producing and using lightly filtered photoplethysmograph signals
US8417310B2 (en) 2009-08-10 2013-04-09 Covidien Lp Digital switching in multi-site sensor
US8428675B2 (en) 2009-08-19 2013-04-23 Covidien Lp Nanofiber adhesives used in medical devices
US8596270B2 (en) * 2009-08-20 2013-12-03 Covidien Lp Systems and methods for controlling a ventilator
US8400149B2 (en) * 2009-09-25 2013-03-19 Nellcor Puritan Bennett Ireland Systems and methods for gating an imaging device
US8498683B2 (en) 2010-04-30 2013-07-30 Covidien LLP Method for respiration rate and blood pressure alarm management
US8834378B2 (en) 2010-07-30 2014-09-16 Nellcor Puritan Bennett Ireland Systems and methods for determining respiratory effort
US8888701B2 (en) 2011-01-27 2014-11-18 Valencell, Inc. Apparatus and methods for monitoring physiological data during environmental interference
US9109902B1 (en) 2011-06-13 2015-08-18 Impact Sports Technologies, Inc. Monitoring device with a pedometer
EP2739207B1 (en) 2011-08-02 2017-07-19 Valencell, Inc. Systems and methods for variable filter adjustment by heart rate metric feedback
CN104168828A (en) 2012-01-16 2014-11-26 瓦伦赛尔公司 Physiological metric estimation rise and fall limiting
JP6116017B2 (en) 2012-01-16 2017-04-19 ヴァレンセル,インコーポレイテッドValencell, Inc. Reduction of physiological measurement error by inertia rhythm
KR102025571B1 (en) * 2012-07-27 2019-09-27 삼성전자주식회사 Apparatus and method for measuring change in blood pressure caused by breathing control
US9078575B2 (en) 2013-10-30 2015-07-14 Apn Health, Llc Heartbeat categorization
US9179849B1 (en) 2014-07-25 2015-11-10 Impact Sports Technologies, Inc. Mobile plethysmographic device
US10328202B2 (en) * 2015-02-04 2019-06-25 Covidien Lp Methods and systems for determining fluid administration
US10499835B2 (en) 2015-03-24 2019-12-10 Covidien Lp Methods and systems for determining fluid responsiveness in the presence of noise
US9801587B2 (en) 2015-10-19 2017-10-31 Garmin Switzerland Gmbh Heart rate monitor with time varying linear filtering
US10610158B2 (en) 2015-10-23 2020-04-07 Valencell, Inc. Physiological monitoring devices and methods that identify subject activity type
US10945618B2 (en) 2015-10-23 2021-03-16 Valencell, Inc. Physiological monitoring devices and methods for noise reduction in physiological signals based on subject activity type
US10966662B2 (en) 2016-07-08 2021-04-06 Valencell, Inc. Motion-dependent averaging for physiological metric estimating systems and methods
JP7146733B2 (en) * 2016-07-18 2022-10-04 ビオプティックス・インコーポレイテッド Oxygen measurement device with laparoscopic dilation
EP3624690B1 (en) 2017-05-15 2023-12-20 Agency for Science, Technology and Research Method and system for respiratory measurement

Family Cites Families (61)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3704706A (en) 1969-10-23 1972-12-05 Univ Drexel Heart rate and respiratory monitor
US4306567A (en) 1977-12-22 1981-12-22 Krasner Jerome L Detection and monitoring device
US4379460A (en) 1980-09-18 1983-04-12 Judell Neil H K Method and apparatus for removing cardiac artifact in impedance plethysmographic respiration monitoring
US4404974A (en) 1981-08-07 1983-09-20 Possis Medical, Inc. Method and apparatus for monitoring and displaying heart rate and blood pressure product information
US4510944A (en) 1982-12-30 1985-04-16 Porges Stephen W Method and apparatus for evaluating rhythmic oscillations in aperiodic physiological response systems
US4781201A (en) 1984-12-27 1988-11-01 American Home Products Corporation (Del.) Cardiovascular artifact filter
JPS61228831A (en) 1985-04-02 1986-10-13 ミノルタ株式会社 Apparatus for detecting non-respiration fit
DE3536491A1 (en) 1985-10-12 1987-04-16 Morgenstern Juergen DEVICE FOR MONITORING BREATHABILITY AND HEART ACTIVITY
DE3604986A1 (en) 1986-02-17 1987-08-20 Hellige Gmbh DEVICE FOR PREVENTING OXYGEN LACK DAMAGE
US4777960A (en) 1986-08-18 1988-10-18 Massachusetts Institute Of Technology Method and apparatus for the assessment of autonomic response by broad-band excitation
US4899760A (en) 1987-06-15 1990-02-13 Colin Electronics Co., Ltd. Noise rejecting detector for biomedical signals
US4860759A (en) 1987-09-08 1989-08-29 Criticare Systems, Inc. Vital signs monitor
US4863265A (en) 1987-10-16 1989-09-05 Mine Safety Appliances Company Apparatus and method for measuring blood constituents
US4858638A (en) 1987-11-10 1989-08-22 Sloan Valve Company Fast-acting quick release valve
US5078136A (en) 1988-03-30 1992-01-07 Nellcor Incorporated Method and apparatus for calculating arterial oxygen saturation based plethysmographs including transients
US4869254A (en) 1988-03-30 1989-09-26 Nellcor Incorporated Method and apparatus for calculating arterial oxygen saturation
JPH06169902A (en) 1988-05-05 1994-06-21 Sentinel Monitoring Inc Pulse type non-invasion type oxymeter and technology for measuring it
US4972842A (en) 1988-06-09 1990-11-27 Vital Signals, Inc. Method and apparatus for precision monitoring of infants on assisted ventilation
US4958638A (en) 1988-06-30 1990-09-25 Georgia Tech Research Corporation Non-contact vital signs monitor
US4960129A (en) 1988-12-05 1990-10-02 Trustees Of The University Of Pennsylvania Methods of observing autonomic neural stimulation and diagnosing cardiac dynamical dysfunction using heartbeat interval data to analyze cardioventilatory interactions
US5111817A (en) 1988-12-29 1992-05-12 Medical Physics, Inc. Noninvasive system and method for enhanced arterial oxygen saturation determination and arterial blood pressure monitoring
US5423322A (en) 1988-12-29 1995-06-13 Medical Physics, Inc. Total compliance method and apparatus for noninvasive arterial blood pressure measurement
US5511553A (en) 1989-02-15 1996-04-30 Segalowitz; Jacob Device-system and method for monitoring multiple physiological parameters (MMPP) continuously and simultaneously
US5033472A (en) 1989-02-23 1991-07-23 Nihon Kohden Corp. Method of and apparatus for analyzing propagation of arterial pulse waves through the circulatory system
US5902235A (en) 1989-03-29 1999-05-11 Somanetics Corporation Optical cerebral oximeter
US4930517A (en) 1989-04-25 1990-06-05 Massachusetts Institute Of Technology Method and apparatus for physiologic system identification
DE68916803T2 (en) 1989-12-23 1994-10-27 Hewlett Packard Gmbh Method for obtaining a respiratory signal and / or a cardiac disturbance signal from a physiological signal.
SE465551B (en) 1990-02-16 1991-09-30 Aake Oeberg DEVICE FOR DETERMINING A HEART AND RESPIRATORY FREQUENCY THROUGH PHOTOPLETISMOGRAPHICAL SEATING
US5490505A (en) 1991-03-07 1996-02-13 Masimo Corporation Signal processing apparatus
EP1357481A3 (en) 1991-03-07 2005-04-27 Masimo Corporation Signal processing apparatus and method
US5273036A (en) 1991-04-03 1993-12-28 Ppg Industries, Inc. Apparatus and method for monitoring respiration
US5934277A (en) 1991-09-03 1999-08-10 Datex-Ohmeda, Inc. System for pulse oximetry SpO2 determination
ATE172623T1 (en) 1991-12-17 1998-11-15 Dynamics Imaging Inc METHOD AND DEVICE FOR DIAGNOSING LIVING ORGANISMS
US5818048A (en) 1992-07-15 1998-10-06 Optix Lp Rapid non-invasive optical analysis using broad bandpass spectral processing
JPH0638965A (en) 1992-07-23 1994-02-15 Minolta Camera Co Ltd Respiration diagnostic apparatus
US5368224A (en) 1992-10-23 1994-11-29 Nellcor Incorporated Method for reducing ambient noise effects in electronic monitoring instruments
JP2979933B2 (en) 1993-08-03 1999-11-22 セイコーエプソン株式会社 Pulse wave analyzer
US5553615A (en) 1994-01-31 1996-09-10 Minnesota Mining And Manufacturing Company Method and apparatus for noninvasive prediction of hematocrit
US5575284A (en) 1994-04-01 1996-11-19 University Of South Florida Portable pulse oximeter
US5853364A (en) 1995-08-07 1998-12-29 Nellcor Puritan Bennett, Inc. Method and apparatus for estimating physiological parameters using model-based adaptive filtering
US5980463A (en) 1995-09-28 1999-11-09 Data Sciences International, Inc. Method for respiratory tidal volume measurement
IL116020A (en) 1995-11-16 2000-06-01 Optelmed Ltd Apparatus and method for measuring the variability of cardiovascular parameters
US5766127A (en) 1996-04-15 1998-06-16 Ohmeda Inc. Method and apparatus for improved photoplethysmographic perfusion-index monitoring
JP3666987B2 (en) 1996-05-02 2005-06-29 コーリンメディカルテクノロジー株式会社 Blood pressure monitoring device
US5931779A (en) 1996-06-06 1999-08-03 Wisconsin Alumni Research Foundation Real-time in-vivo measurement of myoglobin oxygen saturation
CN1203805C (en) * 1996-09-10 2005-06-01 精工爱普生株式会社 Organism state measuring device and relaxation instructing device
US5830137A (en) 1996-11-18 1998-11-03 University Of South Florida Green light pulse oximeter
SE9604320D0 (en) 1996-11-25 1996-11-25 Pacesetter Ab Medical device
US5842979A (en) 1997-02-14 1998-12-01 Ohmeda Inc. Method and apparatus for improved photoplethysmographic monitoring of oxyhemoglobin, deoxyhemoglobin, carboxyhemoglobin and methemoglobin
JP2956833B2 (en) 1997-02-19 1999-10-04 日本電気株式会社 Evaluation method of polycrystalline silicon film
US5954644A (en) 1997-03-24 1999-09-21 Ohmeda Inc. Method for ambient light subtraction in a photoplethysmographic measurement instrument
US6002952A (en) 1997-04-14 1999-12-14 Masimo Corporation Signal processing apparatus and method
US5919134A (en) 1997-04-14 1999-07-06 Masimo Corp. Method and apparatus for demodulating signals in a pulse oximetry system
US5865756A (en) 1997-06-06 1999-02-02 Southwest Research Institute System and method for identifying and correcting abnormal oscillometric pulse waves
US5971930A (en) 1997-10-17 1999-10-26 Siemens Medical Systems, Inc. Method and apparatus for removing artifact from physiological signals
US6099481A (en) 1997-11-03 2000-08-08 Ntc Technology, Inc. Respiratory profile parameter determination method and apparatus
US6155992A (en) 1997-12-02 2000-12-05 Abbott Laboratories Method and apparatus for obtaining interstitial fluid for diagnostic tests
JP3213278B2 (en) 1998-05-12 2001-10-02 日本コーリン株式会社 Non-invasive continuous blood pressure estimation device
US5997482A (en) 1998-06-01 1999-12-07 Vaschillo; Evgeny G. Therapeutic method for a human subject
US6129675A (en) 1998-09-11 2000-10-10 Jay; Gregory D. Device and method for measuring pulsus paradoxus
US6480733B1 (en) 1999-11-10 2002-11-12 Pacesetter, Inc. Method for monitoring heart failure

Cited By (88)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060004405A1 (en) * 2001-10-18 2006-01-05 Amr Salahieh Vascular embolic filter devices and methods of use therefor
US20050209521A1 (en) * 2002-05-29 2005-09-22 Joni Kettunen Procedure for deriving reliable information on respiratory activity from heart period measurement
US7460901B2 (en) * 2002-05-29 2008-12-02 Firstbeat Technologies Oy Procedure for deriving reliable information on respiratory activity from heart period measurement
US20040225207A1 (en) * 2003-05-09 2004-11-11 Sang-Kon Bae Ear type apparatus for measuring a bio signal and measuring method therefor
US7209775B2 (en) * 2003-05-09 2007-04-24 Samsung Electronics Co., Ltd. Ear type apparatus for measuring a bio signal and measuring method therefor
US8343057B2 (en) * 2003-12-01 2013-01-01 Ric Investments, Llc Apparatus and method for monitoring pressure related changes in the extra-thoracic arterial circulatory system
US20100222655A1 (en) * 2003-12-01 2010-09-02 Ric Investments, Llc Apparatus and method for monitoring pressure related changes in the extra-thoracic arterial circulatory system
EP3066978A1 (en) * 2003-12-30 2016-09-14 Beta Biomed Services, Inc. Method and system of monitoring respiration in an individual
US20070021673A1 (en) * 2004-01-27 2007-01-25 Cardiometer Ltd. Method and system for cardiovascular system diagnosis
US20100174200A1 (en) * 2004-03-18 2010-07-08 Respironics, Inc. Methods and devices for relieving stress
US7691049B2 (en) 2004-03-18 2010-04-06 Respironics, Inc. Methods and devices for relieving stress
US8938288B2 (en) * 2004-03-18 2015-01-20 Respironics, Inc. Methods and devices for relieving stress
US8641631B2 (en) 2004-04-08 2014-02-04 Masimo Corporation Non-invasive monitoring of respiratory rate, heart rate and apnea
US7139701B2 (en) 2004-06-30 2006-11-21 Motorola, Inc. Method for detecting and attenuating inhalation noise in a communication system
US7254535B2 (en) 2004-06-30 2007-08-07 Motorola, Inc. Method and apparatus for equalizing a speech signal generated within a pressurized air delivery system
US7155388B2 (en) 2004-06-30 2006-12-26 Motorola, Inc. Method and apparatus for characterizing inhalation noise and calculating parameters based on the characterization
US20060020451A1 (en) * 2004-06-30 2006-01-26 Kushner William M Method and apparatus for equalizing a speech signal generated within a pressurized air delivery system
US20060009970A1 (en) * 2004-06-30 2006-01-12 Harton Sara M Method for detecting and attenuating inhalation noise in a communication system
US20060009971A1 (en) * 2004-06-30 2006-01-12 Kushner William M Method and apparatus for characterizing inhalation noise and calculating parameters based on the characterization
US9668695B2 (en) 2004-08-11 2017-06-06 University Of Florida Research Foundation, Inc. Pulse oximeter probes and methods for using the same
US11259749B2 (en) 2004-08-11 2022-03-01 Koninklijke Philips N.V. Pulse oximeter probes and methods for using the same
US20070056582A1 (en) * 2005-03-18 2007-03-15 Michael Wood Methods and devices for relieving stress
US8002711B2 (en) 2005-03-18 2011-08-23 Respironics, Inc. Methods and devices for relieving stress
US8428702B2 (en) 2005-03-18 2013-04-23 Respironics, Inc. Methods and devices for relieving stress
US7438688B2 (en) 2005-08-26 2008-10-21 Nihon Kohden Corporation Apparatus and method for measuring pulse rate
EP1757225A1 (en) * 2005-08-26 2007-02-28 Nihon Kohden Corporation Apparataus and method for measuring pulse rate
GB2438070A (en) * 2006-05-12 2007-11-14 Suunto Oy Determining energy consumption during exercise from respiratory frequency derived from heart rate measurements
GB2438070B (en) * 2006-05-12 2010-11-17 Suunto Oy Method, Device and computer program product for monitoring the physiological state of a person
US11229374B2 (en) 2006-12-09 2022-01-25 Masimo Corporation Plethysmograph variability processor
US20100004552A1 (en) * 2006-12-21 2010-01-07 Fresenius Medical Care Deutschland Gmbh Method and device for the determination of breath frequency
US7922664B2 (en) * 2007-04-05 2011-04-12 Coherence Llc Method and system for improving physiologic status and health via assessment of the dynamic respiratory arterial pressure wave using plethysmographic technique
US20080249422A1 (en) * 2007-04-05 2008-10-09 Stephen Bennett Elliott Method and system for improving physiologic status and health via assessment of the dynamic respiratory arterial pressure wave using plethysmographic technique
US20100298730A1 (en) * 2007-07-30 2010-11-25 Oxford Biosignals Limited Method and apparatus for measuring breathing rate
US8465434B2 (en) * 2007-12-06 2013-06-18 Los Angeles Biomedical Research Institute At Harbor-Ucla Medical Center Method and system for detection of respiratory variation in plethysmographic oximetry
US20120172688A1 (en) * 2007-12-06 2012-07-05 Los Angeles Biomedical Research Institute At Harbor-Ucla Medical Center Method and system for detection of respiratory variation in plethysmographic oximetry
US8398555B2 (en) 2008-09-10 2013-03-19 Covidien Lp System and method for detecting ventilatory instability
US20100106030A1 (en) * 2008-10-23 2010-04-29 Mason Gregory R Method and system for automated measurement of pulsus paradoxus
US8515513B2 (en) 2008-11-05 2013-08-20 Covidien Lp System and method for facilitating observation of monitored physiologic data
US20100113904A1 (en) * 2008-11-05 2010-05-06 Nellcor Puritan Bennett Llc System And Method For Facilitating Observation Of Monitored Physiologic Data
US9351665B2 (en) 2009-01-14 2016-05-31 Widemed Technologies Ltd. Method and system for detecting a respiratory signal
WO2010082200A1 (en) * 2009-01-14 2010-07-22 Widemed Ltd. Method and system for detecting a respiratory signal
US9877686B2 (en) 2009-10-15 2018-01-30 Masimo Corporation System for determining confidence in respiratory rate measurements
US9066680B1 (en) 2009-10-15 2015-06-30 Masimo Corporation System for determining confidence in respiratory rate measurements
US10813598B2 (en) 2009-10-15 2020-10-27 Masimo Corporation System and method for monitoring respiratory rate measurements
US9848800B1 (en) 2009-10-16 2017-12-26 Masimo Corporation Respiratory pause detector
US10595747B2 (en) 2009-10-16 2020-03-24 Masimo Corporation Respiration processor
US9724016B1 (en) 2009-10-16 2017-08-08 Masimo Corp. Respiration processor
US11399722B2 (en) 2010-03-30 2022-08-02 Masimo Corporation Plethysmographic respiration rate detection
US9307928B1 (en) * 2010-03-30 2016-04-12 Masimo Corporation Plethysmographic respiration processor
US10098550B2 (en) 2010-03-30 2018-10-16 Masimo Corporation Plethysmographic respiration rate detection
US9402554B2 (en) 2011-09-23 2016-08-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9119597B2 (en) 2011-09-23 2015-09-01 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US8880576B2 (en) 2011-09-23 2014-11-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9675274B2 (en) 2011-09-23 2017-06-13 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9737266B2 (en) 2011-09-23 2017-08-22 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9693709B2 (en) 2011-09-23 2017-07-04 Nellcot Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9060746B2 (en) 2011-11-30 2015-06-23 Covidien Lp Systems and methods for detecting arrhythmia from a physiological signal
US8755871B2 (en) 2011-11-30 2014-06-17 Covidien Lp Systems and methods for detecting arrhythmia from a physiological signal
US9693736B2 (en) 2011-11-30 2017-07-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using historical distribution
US9247896B2 (en) 2012-01-04 2016-02-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using phase locked loop
US10376157B2 (en) 2012-01-04 2019-08-13 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using phase locked loop
US11478155B2 (en) 2012-02-24 2022-10-25 Covidien Lp Hypovolemia diagnosis technique
US8880155B2 (en) 2012-02-24 2014-11-04 Covidien Lp Hypovolemia diagnosis technique
US9801579B2 (en) 2012-03-19 2017-10-31 Fujitsu Limited Arousal-level determining apparatus and arousal-level determining method
US9179876B2 (en) 2012-04-30 2015-11-10 Nellcor Puritan Bennett Ireland Systems and methods for identifying portions of a physiological signal usable for determining physiological information
US20140039283A1 (en) * 2012-07-31 2014-02-06 Periodic Breathing Foundation System for analyzing oximetry data
US10631738B2 (en) * 2012-07-31 2020-04-28 The Periodic Breathing Foundation, Llc System for analyzing oximetry data
US9560978B2 (en) 2013-02-05 2017-02-07 Covidien Lp Systems and methods for determining respiration information from a physiological signal using amplitude demodulation
US9687159B2 (en) 2013-02-27 2017-06-27 Covidien Lp Systems and methods for determining physiological information by identifying fiducial points in a physiological signal
US9554712B2 (en) 2013-02-27 2017-01-31 Covidien Lp Systems and methods for generating an artificial photoplethysmograph signal
US10441181B1 (en) 2013-03-13 2019-10-15 Masimo Corporation Acoustic pulse and respiration monitoring system
US10022068B2 (en) 2013-10-28 2018-07-17 Covidien Lp Systems and methods for detecting held breath events
US9848820B2 (en) 2014-01-07 2017-12-26 Covidien Lp Apnea analysis system and method
US10537289B2 (en) 2014-02-20 2020-01-21 Covidien Lp Systems and methods for filtering autocorrelation peaks and detecting harmonics
US9901308B2 (en) 2014-02-20 2018-02-27 Covidien Lp Systems and methods for filtering autocorrelation peaks and detecting harmonics
US20160143566A1 (en) * 2014-11-20 2016-05-26 Qualcomm Incorporated Circuitry to Allow Low Current Operation of a Device Capable of Determining a Blood Property
US9743868B2 (en) * 2014-11-20 2017-08-29 Qualcomm Incorporated Circuitry to allow low current operation of a device capable of determining a blood property
US20190261890A1 (en) * 2015-06-01 2019-08-29 Pixart Imaging Inc. Optical respiration rate detection device
US20230293041A1 (en) * 2015-06-01 2023-09-21 Pixart Imaging Inc. Optical respiration rate detection device capable of determining denoising range
US11701027B2 (en) * 2015-06-01 2023-07-18 Pixart Imaging Inc. Optical respiration rate detection device
US10159842B2 (en) 2015-08-28 2018-12-25 Cardiac Pacemakers, Inc. System and method for detecting tamponade
US10589101B2 (en) 2015-08-28 2020-03-17 Cardiac Pacemakers, Inc. System and method for detecting tamponade
US10856743B2 (en) * 2015-08-28 2020-12-08 Oslermd, Inc. Methods and apparatuses for measuring multiple vital signs based on arterial pressure waveforms
US20170055846A1 (en) * 2015-08-28 2017-03-02 Oslermd, Inc. Methods and apparatuses for measuring multiple vital signs based on arterial pressure waveforms
US20180333102A1 (en) * 2015-12-01 2018-11-22 Koninklijke Philips N.V. Device, system and method for determining vital sign information of a subject
CN106725491A (en) * 2017-02-16 2017-05-31 王丽燕 A kind of respiratory rate method for determining child patient
US11272859B1 (en) 2020-08-20 2022-03-15 Cloud Dx, Inc. System and method of determining respiratory status from oscillometric data
US11006843B1 (en) 2020-08-20 2021-05-18 Cloud Dx, Inc. System and method of determining breathing rates from oscillometric data

Also Published As

Publication number Publication date
US6702752B2 (en) 2004-03-09

Similar Documents

Publication Publication Date Title
US6702752B2 (en) Monitoring respiration based on plethysmographic heart rate signal
US6805673B2 (en) Monitoring mayer wave effects based on a photoplethysmographic signal
US6896661B2 (en) Monitoring physiological parameters based on variations in a photoplethysmographic baseline signal
US7001337B2 (en) Monitoring physiological parameters based on variations in a photoplethysmographic signal
US6002952A (en) Signal processing apparatus and method
US10098550B2 (en) Plethysmographic respiration rate detection
US6178343B1 (en) Pulse rate and heart rate coincidence detection for pulse oximetry
US6709402B2 (en) Apparatus and method for monitoring respiration with a pulse oximeter
US20210030372A1 (en) Methods to estimate the blood pressure and the arterial stiffness based on photoplethysmographic (ppg) signals
EP0335357B1 (en) Improved method and apparatus for detecting optical pulses
US6990426B2 (en) Diagnostic method and apparatus using light
US7403806B2 (en) System for prefiltering a plethysmographic signal
US20080167541A1 (en) Interference Suppression in Spectral Plethysmography
US20060293574A1 (en) Separating oximeter signal components based on color
Tanveejul et al. A Study on the Subject and Location Specificity in Reflectance based SpO 2 Estimation using R-value based Calibration Curve
Samimi et al. Cuffless blood pressure estimation using cardiovascular dynamics
KR20060054644A (en) Method for eliminating motion artifact in pulse oximetry
Qananwah et al. Monitoring Blood Pressure Using Regression Techniques

Legal Events

Date Code Title Description
AS Assignment

Owner name: DATEX-OHMEDA, INC., WISCONSIN

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:DEKKER, ANDREAS LUBBERTUS ALOYSIUS JOHANNES;REEL/FRAME:012959/0187

Effective date: 20020507

STCF Information on status: patent grant

Free format text: PATENTED CASE

FEPP Fee payment procedure

Free format text: PAYOR NUMBER ASSIGNED (ORIGINAL EVENT CODE: ASPN); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Free format text: PAYER NUMBER DE-ASSIGNED (ORIGINAL EVENT CODE: RMPN); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

FPAY Fee payment

Year of fee payment: 4

FPAY Fee payment

Year of fee payment: 8

FPAY Fee payment

Year of fee payment: 12